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LatestMicrosoftCowork
MicrosoftVision-Language

Microsoft's Mage-VL-Cowork takes on computer-use tasks

A new vision-language agent model aims to operate GUIs, write code, and work the terminal.

Oct 30, 2026
NotableOther
Mage-VL-Cowork

Microsoft has published Mage-VL-Cowork, a vision-language model built to act as a computer-use agent, on Hugging Face. Rather than simply describing images, the model is designed to take actions — navigating graphical interfaces, writing and running code, and operating a terminal.

The release reflects a broader shift in open-weight AI toward agentic systems that can perceive a screen and manipulate it directly. Where earlier vision-language models focused on captioning and visual question answering, this generation of "computer-use" models treats the desktop itself as the environment to be understood and controlled.

What it targets

  • GUI interaction, including clicking through and navigating on-screen interfaces
  • Coding tasks that combine visual context with code generation
  • Terminal and command-line workflows

Microsoft has not published parameter counts, context length, or benchmark figures alongside the initial listing, and the model carries a non-standard "other" license, so teams evaluating it for production should review the terms on the model card carefully.

Why it matters: computer-use agents are one of the most contested frontiers in applied AI, with closed offerings from several major labs. An openly available model aimed at the same GUI-and-terminal territory gives researchers and developers a base to study, fine-tune, and benchmark against — assuming the licensing fits their use. More details are on the Hugging Face repository.

Sources

  • microsoft/Mage-VL-Cowork

    Hugging Face

    Visit
OlderIBM's Granite Switch Treats Models Like SoftwareIBM · Any-to-Any · 3 days ago

Get the model

Hugging Face

Specs

Context window262K tokens
Size9.5 GB
PrecisionBF16
Architecturellava_onevision2
LicenseOTHER
Downloads752
Likes121

Can you run it?

Runs on a laptop — about 5.1 GB at 4-bit.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    11.7 GB
  • 8-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    7.2 GB
  • 4-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.1 GB
Your machine
GGUF builds
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Vision-Language

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